class_docstr: Standalone Multiply-and-accumulate metric. Provides a lower bound of the
  computational cost of a model in a hardware-independent way by
  computing the number of multiplications. Currently supports only
  Linear or Conv2d modules. Other operations are ignored.
code: def is_recognized_module(mod):
      modname = mod.__class__.__name__
      return modname == "Linear" or modname == "Conv2d"
  
imports: from torch.nn import Module
  from typing import List, Optional
  from torch import Tensor
  from avalanche.evaluation import Metric, PluginMetric, GenericPluginMetric
label_desc: Use image node_id 6 for calling the MAC obj's underlying member method code with example usage: obj.is_recognized_module(mod) and returns: unknown